M. TURNER James, HUDON Michele, DEVIN Yves. Organizing moving image collections for the digital era : the goldspeil report". Information Outlook. August 2002. FindArticles.com. 15 Feb. 2007.
DC Title : Organizing moving image collections for the digital era: the goldspeil report
D.C Creator : M. TURNER James, HUDON Michele, DEVIN Yvest
D.C Subject : digital image/images collections/moving image/organization/research/retrieval/storage/support
D.C Description : this text explains the goal which is to understand the techniques and tools used for representing the content of moving image collections that are indexed shot by shot.
D.C Publisher : nformation outlook
D.C Date : August 2002
D.C Type : Text
D.C Format :html.
D.C Identifier : http://www.findarticles.com/p/articles/mi_m0FWE/is_8_6/ai_90932749
D.C Source : http://www.findarticles.com/
D.C Coverage : -
This text is an extract of the original text.
Organizing moving image collections for the digital era : the goldspeil report
"THE STEVEN I. GOLDSPIEL MEMORIAL RESEARCH FUND WAS ESTABLISHED IN 1991, and named in honor of the former president of Disclosure, Inc. (now known as Primark). The research fund is an endowment and projects are funded solely from investment income generated by the fund. The purpose of the fund is to support projects that promote research and advancement of library sciences, in particular focusing on projects that address the goals identified in the SLA Research Statement.
The 1999 winners of the award were James M. Turner, Michele Hudon and Yves Devin from the Universite de Montreal. The results of their project titled, "Organizing Moving Image Collections for the Digital Era" are presented here.
Introduction
Pictures have always been used to represent concepts and ideas and to communicate messages. Now that we collect them so extensively, we need to represent the pictures themselves in order to store and retrieve them. Photography, movies, television and digital images stored on computers have all contributed to the rapid buildup of ever larger collections. Whatever the format or the presentation medium, pictures have become a most important mode of communication in our time. They play a crucial role in such areas as medicine, journalism, advertising, education and entertainment. The notion of picture collections now has to do with a vast world, and an attempt to describe this world is represented by the study poster entitled The World of Visual Collections (GRIV 1998), which takes into account the areas of art, engraving, photography, computer graphics, the types of institutions which collect and the many professions that use pictures as part of their work.
Moving images are, of course, a goldmine for many organizations and individuals, and it is important to describe them adequately in databases in order to show their richness and complexity if we are to exploit these collections fully. However, the world of moving image collection organization is one of locally established techniques, with little or no standardization and without communicability between systems. This has not been a problem until now because systems were managed independently of each other, but in the networked world in which we now live, the question of discovery and exchange of information has come to the forefront and needs to be addressed.
Our recently-completed research project was concerned with indexing moving image collections for storage and retrieval. The general goal of the project was to understand the techniques and tools used for representing the content of moving image collections that are indexed shot by shot. We especially wanted to study the question of indexing languages and their structure, as well as techniques for keeping them current. Several more specific objectives were identified:
* to determine how many terms, excluding proper names, are used to describe North American moving image collections indexed at the shot level;
* to estimate the rate of growth of term creation in these tools;
* to discover to what degree the lexical concepts are similar among the various tools; and
* to evaluate the possibility of creating a universal indexing vocabulary for general collections of moving images, those that represent everyday objects and events.
In this article we look at the background information to the study, after which we describe the method used to collect the data. The results are then given along with discussion of them, followed by conclusions we might draw from this research.
Background
Both still and moving images can be divided into three broad categories: art images, documentary images and "ordinary" images, each requiring its own type of organization. The proliferation of supports and the changing context (brought about first by the arrival of computer technology and then the networking of resources) are the driving forces behind a great deal of work in retooling and rethinking work methods, but they do not change this fundamental (if arbitrary) classification. Nor does the shift from analogue to digital images. Thus, there is a great deal of work to do, but the guiding principles remain the same.
The many new systems and ever more efficient technologies for capturing and processing moving images require the establishment of effective management systems. It is necessary to be able to find any specific shot in a particular collection rapidly and efficiently. Without the establishment of new methods for storage and retrieval of moving images, these valuable resources will get lost in a hopeless jumble of useless data.
Research in the area of storage and retrieval of moving images takes place using two distinct approaches with little in common (Cawkell 1992, 180). The low-level or content-based approach is the focus of work by computer science researchers. This approach involves the statistical manipulation of pixels to get information about color preponderance and arrangement, recognition of textures, patterns, boundaries, objects, scene detection and so on. The high-level or concept-based approach is the focus of work by information science researchers. This approach involves human generation of metadata substantially assisted by computer technology (semi-automatic), as well as automatic generation of high-level metadata. The general focus of this approach is finding ways to generate shot-level indexing automatically from text created during the pre-production, production, and post-production stages, such as closed captioning, audio description, and production scripts. The two research streams are complementary, and the b est information systems for storage and retrieval of moving images will need to incorporate both approaches."[...]
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